doc fix

TuringLang · Sep 17, 2021 · 75d5e9c · 75d5e9c
1 parent 41d55c5
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Showing 4 changed files with 19 additions and 16 deletions.
diff --git a/src/InternalHelpers.jl b/src/InternalHelpers.jl
@@ -14,6 +14,11 @@ of that point. This function must take the form `f(θ[1], ..., θ[n], data)`, wh
 parameter vector. See also the `splat` keyword argument.
 """
 
+const LIKELIHOOD_ARRAY_ARG = """
+`log_likelihood::Array`: A matrix or 3d array of log-likelihood values indexed as
+`[data, step, chain]`. See the `chain_index` argument if leaving the `chain` index off.
+"""
+
 const R_EFF_DOC = """
 `r_eff::AbstractVector`: An (optional) vector of relative effective sample sizes used in ESS 
 calculations. If left empty, calculated automatically using the FFTESS method from 

diff --git a/src/LeaveOneOut.jl b/src/LeaveOneOut.jl
@@ -99,9 +99,7 @@ score.
 
 # Arguments
 
-  - `log_likelihood::Array`: A matrix or 3d array of log-likelihood values indexed as
-    `[data, step, chain]`. The chain argument can be left off if `chain_index` is provided
-    or if all posterior samples were drawn from a single chain.
+  - $LIKELIHOOD_ARRAY_ARG
   - $ARGS [`psis`](@ref).
   - $CHAIN_INDEX_DOC
   - $KWARGS [`psis`](@ref).
@@ -135,11 +133,9 @@ Use a precalculated `Psis` object to estimate the leave-one-out cross validation
 
 # Arguments
 
-    - `log_likelihood::Array`: A matrix or 3d array of log-likelihood values indexed as
-      `[data, step, chain]`. The chain argument can be left off if `chain_index` is provided
-      or if all posterior samples were drawn from a single chain.
-    - `psis_object`: A precomputed `Psis` object used to estimate the LOO-CV score.
-    - $CHAIN_INDEX_DOC
+  - $LIKELIHOOD_ARRAY_ARG
+  - `psis_object`: A precomputed `Psis` object used to estimate the LOO-CV score.
+  - $CHAIN_INDEX_DOC
 
 See also: [`psis`](@ref), [`loo`](@ref), [`PsisLoo`](@ref).
 

diff --git a/src/ModelComparison.jl b/src/ModelComparison.jl
@@ -4,12 +4,6 @@ import Base.show
 
 export loo_compare, ModelComparison
 
-const LOO_COMPARE_KWARGS = """
-- `model_names`: A vector or tuple of strings or symbols used to identify models. If
-none, models are numbered using the order of the arguments.
-- `sort_models`: Sort models by total score.
-- `high_to_low`: Sort models from best to worst score. If `false`, reverse the order.
-"""
 
 """
     ModelComparison
@@ -65,7 +59,10 @@ Construct a model comparison table from several [`PsisLoo`](@ref) objects.
   - `cv_results`: One or more [`PsisLoo`](@ref) objects to be compared. Alternatively,
     a tuple or named tuple of `PsisLoo` objects can be passed. If a named tuple is passed,
     these names will be used to label each model. 
-  - $LOO_COMPARE_KWARGS
+  - `model_names`: A vector or tuple of strings or symbols used to identify models. If
+    none, models are numbered using the order of the arguments.
+  - `sort_models`: Sort models by total score.
+  - `high_to_low`: Sort models from best to worst score. If `false`, reverse the order.
 
 See also: [`ModelComparison`](@ref), [`PsisLoo`](@ref), [`psis_loo`](@ref)
 """

diff --git a/src/NaiveLPD.jl b/src/NaiveLPD.jl
@@ -3,9 +3,13 @@ using Tullio
 
 
 """
-    $(TYPEDSIGNATURES)
+    naive_lpd(log_likelihood::AbstractArray{<:Real}, chain_index::Vector}<:Int)
 Calculate the naive (in-sample) estimate of the expected log probability density, otherwise
 known as the in-sample Bayes score. Not recommended for most uses.
+
+# Arguments
+  - $LIKELIHOOD_ARRAY_ARG
+  - $CHAIN_INDEX_DOC
 """
 function naive_lpd(log_likelihood::AbstractArray{<:Real, 3})
     @info "We advise against using `naive_lpd`, as it gives inconsistent and strongly " *
@@ -18,6 +22,7 @@ function naive_lpd(
     log_likelihood::AbstractMatrix{<:Real}, 
     chain_index::AbstractVector{<:Integer} = _assume_one_chain(log_likelihood)
 )
+    @nospecialize(chain_index)
     log_likelihood = _convert_to_array(log_likelihood, chain_index)
     return _naive_lpd(log_likelihood)
 end